In the highly information-oriented society, with advances in information processing and communication technologies, there is being provided an environment in which an enormous amount of computerized information can be easily acquired. The information acquired by using such an environment is also enormous in data amount, and hence desired information needs to be efficiently and accurately comprehended. As a technique of analyzing the contents of information, a technique of classifying documents constituting each piece of information in accordance with the contents of the documents has been studied.
As a technique of classifying documents, there has been proposed a technique of preparing labels indicating the contents of classifications in advance, analyzing the contents of the respective documents according to a predetermined algorithm, and classifying the respective documents for each prepared label (for example, Masaaki Nagata, “Text Classification—Learning Theory Sample Fair”, Johoshori, Volume 42, first issue, January, 2001). According to such a technique, when documents are to be classified, labels indicating the contents of classifications are prepared, and the labels are accurately assigned to the respective documents by using various kinds of learning algorithms, thereby classifying the respective documents for each label.